Method and system for testing adaptability of hydrogen production at sea by pem electrolyzer

Abstract

The application belongs to the technical field of offshore electrolytic water hydrogen production, and specifically provides a PEM electrolytic tank offshore hydrogen production adaptability test method and a test system. The method comprises the following steps: obtaining a high-frequency fluctuating wind speed time sequence with a frequency not lower than 10 Hz according to wind field data of a target sea area; mapping the wind field to a virtual sea wave field according to the wind field data and the high-frequency fluctuating wind speed time sequence to obtain an instantaneous wave surface elevation sequence; establishing a dynamics model of a hydrogen production platform, and combining the instantaneous wave surface elevation sequence to solve multi-degree-of-freedom motion time history data of the hydrogen production platform; mapping meteorological characteristics to output power of power generation equipment based on a power model of the power generation equipment; taking the multi-degree-of-freedom motion time history data as a control input source of a multi-degree-of-freedom platform, and taking the output power data as a control input source of a power source, so as to synchronously simulate mechanical fluctuation of sea waves and fluctuation of power source load. The application can solve the problem that there is currently a lack of an electrolytic tank test system for an offshore hydrogen production scene.

Description

Technical Field

[0001] This application belongs to the field of marine water electrolysis hydrogen production technology, and more specifically, relates to a test method and test system for the adaptability of PEM electrolyzers to marine hydrogen production. Background Technology

[0002] Hydrogen energy, as a clean energy source with great development potential, has seen proton exchange membrane (PEM) water electrolysis technology, with its high dynamic response characteristics, achieve efficient coupling with clean energy sources, becoming one of the core technological pathways for green hydrogen production. Offshore areas possess abundant renewable energy resources (wind power, photovoltaic power, etc.), but these energy sources face grid connection challenges, providing an ideal scenario for green hydrogen production—water electrolysis for hydrogen production requires significant electricity, which can fully utilize offshore renewable energy resources. However, offshore hydrogen production scenarios face the dual coupling effects of wave motion and power fluctuations, transforming the electrolyzer's operating environment from a traditional steady-state state to a complex dynamic condition. This poses a severe challenge to the electrolyzer's adaptability to the scenario and places higher demands on the specialized development of electrolyzers for this purpose. Related development work urgently requires a large amount of key performance parameters as data support, but currently, there is a lack of electrolyzer testing systems and solutions specifically for offshore hydrogen production scenarios, particularly lacking the ability to accurately simulate complex offshore operating conditions. Offshore field trials suffer from inherent drawbacks such as cumbersome procedures, low iteration efficiency, and difficulty in covering extreme operating conditions, leading to the core development work of electrolyzers being largely carried out onshore. However, existing onshore electrolyzer testing systems are all fixed installations, simulating power input processes only through DC power supplies, lacking dedicated test benches adapted to offshore clean energy hydrogen production scenarios. On the one hand, there are problems such as the difficulty in collecting sea state data and the difficulty in selecting typical operating conditions, making the onshore simulation testing process complicated and the scenario reproduction extremely low. On the other hand, existing testing systems are mainly used for steady-state performance testing, lacking specialized simulation testing capabilities for offshore hydrogen production scenarios, and cannot meet the testing requirements under dynamic operating conditions. Furthermore, current research on the impact of mechanical motion and power fluctuations on electrolyzers is mostly conducted independently, lacking correlation analysis between the two, which makes it difficult to support the adaptability research of electrolyzers in offshore hydrogen production scenarios. In terms of acquiring ocean wave data, traditional acquisition methods are complex, time-consuming, and economically costly, and the data is easily affected by environmental interference, resulting in insufficient accuracy. Moreover, publicly available ocean wave data are mostly macroscopic in space (tens of kilometers) and statistically analyzed in time (hours), which cannot meet the high-frequency signal accuracy requirements of electrolyzer response characteristic research, further limiting the effectiveness of onshore simulation tests. In summary, existing electrolyzer testing systems and related research suffer from three major shortcomings: First, there is a lack of specialized simulation testing systems adapted to offshore hydrogen production scenarios, and existing equipment, which is mainly based on steady-state testing, cannot reproduce dynamic coupled operating conditions; second, research on the impact of mechanical motion and power fluctuations lacks correlation and is difficult to match the requirements of scenario coupling; and third, it is difficult to acquire high-frequency data on ocean wave fluctuations, and the existing data dimensions and accuracy cannot meet the needs of response characteristic research. Ultimately, this makes it difficult for onshore simulation tests to accurately replicate offshore operating conditions, which seriously restricts the development process of dedicated electrolyzers for offshore scenarios. Summary of the Invention

[0003] In response to the deficiencies or improvement needs of existing technologies, this application provides a PEM electrolyzer for testing its suitability for offshore hydrogen production, aiming to solve the problem of the current lack of an electrolyzer testing system for offshore hydrogen production scenarios. The technical objective of this application is mainly achieved through the following technical solutions.

[0004] On the one hand, this application provides a method for testing the adaptability of PEM electrolyzers for offshore hydrogen production, which includes: Obtain a high-frequency pulsating wind speed time series with a frequency of no less than 10Hz based on wind field data of the target sea area. ; Based on the wind field data of the target sea area and the high-frequency pulsating wind speed time series, the wind field of the target sea area is mapped into a virtual wave field to obtain the instantaneous wave rise sequence. A dynamic model of the hydrogen production platform in the target sea area is established, and the multi-degree-of-freedom motion time history data of the hydrogen production platform in the target sea area is calculated by combining the instantaneous wavefront rise sequence. The meteorological characteristics of the target sea area are mapped to the output power of the offshore power generation equipment based on the power model of the offshore power generation equipment, so as to serve as the power input data of the electrolyzer in the hydrogen production platform. The multi-degree-of-freedom motion time history data and the power input data are aligned on the time scale, and the two are used as the control input source of the multi-degree-of-freedom platform below the electrolytic cell and the control input source of the power supply connected to the electrolytic cell, respectively, to synchronously simulate the mechanical fluctuations of ocean waves and the fluctuations of power load. Then, the physical field parameters during the operation of the electrolytic cell are collected in real time.

[0005] As a further preferred option, the high-frequency pulsating wind speed time series with a frequency of not less than 10Hz obtained from the wind field data of the target sea area includes: The high-frequency pulsating wind speed time series is obtained by directly collecting samples at a sampling frequency of not less than 10Hz in the target sea area; or, after obtaining the low-frequency wind speed data of the target sea area, the wind field data is dynamically downscaled using the Kaimal pulsating wind speed spectrum model to reconstruct and generate the high-frequency pulsating wind speed time series.

[0006] As a further preferred embodiment, the dynamic downscaling of the wind field data using the Kaimal fluctuating wind speed spectrum model includes: Obtain the eastward and northward wind speed components at a predetermined height above sea level, and calculate the average wind speed based on the wind speed components in both directions using a vector method. and weather and wind direction; Construct the Kaimal spectrum of wind energy distribution in the frequency domain and obtain the one-sided power spectral density of the longitudinal fluctuating wind speed component. , The standard deviation of wind speed fluctuation, For turbulence integral scale parameters, This refers to the frequency of pulsating wind. For the single-sided power spectral density A frequency-to-time domain transformation is performed to obtain a pulsating time sequence; The high-frequency pulsating wind speed time sequence is obtained by superimposing the pulsating time sequence with the average wind speed.

[0007] As a further preferred embodiment, mapping the wind field of the target sea area to a virtual wave field based on the wind field data of the target sea area and the high-frequency pulsating wind speed time series to obtain the instantaneous wave rise sequence includes: Based on the wind field data of the target sea area, wave spectrum characteristic parameters are obtained, and Jonswap random wave spectrum is constructed to obtain the instantaneous wave rise sequence.

[0008] As a further preferred embodiment, wave spectrum characteristic parameters are obtained based on wind field data of the target sea area, and a Jonswap random wave spectrum is constructed to obtain the instantaneous wavefront rise sequence, including: Based on the wind field data of the target sea area and the high-frequency pulsating wind speed time series, the significant wave height is calculated using empirical formulas for wind and wave development. Spectral peak period ; Based on the significant wave height and the spectral peak period, a Jonswap random wave spectrum suitable for nearshore sea areas with limited wind path is constructed, with the wave power spectral density being: , The angular frequency of the spectral peak. For peak enhancement factor, The energy balance coefficient, For peak shape parameters, Angular frequency, The gravitational acceleration of the target sea area; For the wave power spectral density The instantaneous wavefront elevation sequence is obtained by performing a frequency domain-to-time domain transformation.

[0009] As a further preferred option, a statistical method is used to calculate the effective wave height for the virtual wave field based on the instantaneous wave rise sequence. ,Will and The comparison is used to evaluate the fidelity of the virtual wave field to the target sea area.

[0010] As a further preferred embodiment, a dynamic model of the hydrogen production platform within the target sea area is established, and the multi-degree-of-freedom motion time history data of the hydrogen production platform within the target sea area is calculated by combining the instantaneous wavefront rise sequence, including: A dynamic model of the hydrogen production platform within the target sea area is established. Based on the wind direction angle information and the installation direction of the hydrogen production platform, the amplitude response operator matrix at the corresponding incident angle is obtained, including the amplitude response operator matrix with respect to angular frequency at six degrees of freedom. Variational amplitude and phase operators ; The wave power spectral density will be analyzed. The wavefront complex spectrum obtained during the frequency-to-time domain transformation is convolved with the amplitude operators of each degree of freedom in the frequency domain to obtain the complex spectrum of the motion components under the corresponding degree of freedom. The complex spectra under each of the above degrees of freedom are subjected to inverse fast Fourier transform to obtain a time-domain motion sequence of not less than 10Hz, and then the attitude matrix of the offshore hydrogen production platform is obtained. The attitude matrix is ​​used as the six-degree-of-freedom time history data of the offshore hydrogen production platform and input into the multi-degree-of-freedom platform to solve the corresponding motion control data.

[0011] As a further preferred embodiment, the meteorological characteristics of the target sea area are mapped to the output power of the offshore power generation equipment based on the power model of the offshore power generation equipment, and used as the power input data for the electrolyzer in the hydrogen production platform, including: The offshore power generation equipment uses a wind turbine. Based on the power characteristic model of the wind turbine, the high-frequency pulsating wind speed time series is mapped to the power generation curve of the wind turbine, which is used as the power input curve of the electrolyzer. Alternatively, the offshore power generation equipment may be a photovoltaic device. Based on the power characteristic model of the photovoltaic device, the solar irradiance data of the target sea area may be mapped to the power generation curve of the photovoltaic device, which may then be used as the power input curve of the electrolyzer. Alternatively, the offshore power generation equipment may employ wind turbines and photovoltaic devices. Based on the power characteristic models of the wind turbines and the photovoltaic devices, the high-frequency pulsating wind speed time series and the solar irradiance data of the target sea area are mapped to the power generation curves of the wind turbines and the photovoltaic devices, respectively. The two power generation curves are superimposed and used as the power input curve of the electrolyzer.

[0012] As a further preferred embodiment, mapping the high-frequency pulsating wind speed time series to the power generation curve of the wind turbine includes: The high-frequency pulsating wind speed time series is mapped to the wind speed at the height of the wind turbine hub using an exponential law. Based on the power output characteristics of the wind turbine, the wind speed at the height of the wind turbine hub is converted into the power generation curve of the wind turbine.

[0013] As a further preferred embodiment, an inertial equation is used to simulate the dynamic response delay when the output power of the fan is transferred to the electrolytic cell, and the simulation output result is used as the actual power input curve of the electrolytic cell.

[0014] On the other hand, this application also provides a PEM electrolyzer for offshore hydrogen production adaptability testing system, used to implement the PEM electrolyzer for offshore hydrogen production adaptability testing method as described above, the testing system comprising: Proton exchange membrane electrolyzer; A six-degree-of-freedom platform, wherein the proton exchange membrane electrolyzer is placed on the six-degree-of-freedom platform and moves together with the six-degree-of-freedom platform to simulate the wave fluctuation conditions of hydrogen production at sea; A liquid supply unit is connected to the proton exchange membrane electrolyzer to supply it with electrolyzed water; A power supply unit is connected to the proton exchange membrane electrolyzer to simulate an offshore power generation device supplying power to the proton exchange membrane electrolyzer. The power supply unit includes a programmable DC power supply, the positive and negative terminals of which are respectively connected to the two ends of the proton exchange membrane electrolyzer via wires. A gas emission unit is connected to the proton exchange membrane electrolyzer to discharge the gas generated by the electrolysis reaction. A sensor monitoring unit is used to collect parameters of the proton exchange membrane electrolyzer during the electrolysis reaction process; The control and display unit is connected to the six-degree-of-freedom platform, the power supply unit, and the sensor monitoring unit to realize the control and signal acquisition of each part of the test system.

[0015] As a further preferred embodiment, the six-degree-of-freedom platform adopts a Stewart mechanism, and the telescopic arms within the Stewart mechanism are all driven by servo motors.

[0016] As a further preferred embodiment, the liquid supply unit includes a water tank, a peristaltic pump, and an ultrapure water filtration device connected in sequence by pipes. The outlet of the ultrapure water filtration device is connected to the inlet of the proton exchange membrane electrolyzer via a pipe, and the outlet of the proton exchange membrane electrolyzer is connected to the return outlet of the water tank via a pipe.

[0017] As a further preferred embodiment, the sensor monitoring unit includes a temperature sensor, a voltage sensor, and a current sensor; the temperature sensor extends into the proton exchange membrane electrolyzer, the voltage sensor is disposed between the positive and negative electrodes of the proton exchange membrane electrolyzer, and the current sensor is disposed on the wire connecting the power supply unit and the proton exchange membrane electrolyzer.

[0018] As a further preferred embodiment, the control and display unit includes a host computer and a programmable logic controller (PLC); the PLC is connected to the six-degree-of-freedom platform, the liquid supply unit, the power supply unit, and the sensor monitoring unit; the host computer is connected to the PLC and the gas emission unit.

[0019] As a further preferred embodiment, the testing system further includes an electrochemical workstation, the test port of which is electrically connected to a wire disposed between the power supply unit and the proton exchange membrane electrolyzer, and the information transmission port of which is electrically connected to the host computer.

[0020] As a further preferred embodiment, the testing system also includes a gas analyzer, the input end of which is connected to the gas emission unit, and the information transmission port of which is electrically connected to the host computer.

[0021] In summary, compared with the prior art, the technical solutions conceived in this application have the following main technical advantages: 1. The PEM electrolyzer marine hydrogen production adaptability testing method and testing system described in this application can be driven by a single data source of wind field in the target sea area, and has strong coherence and consistency at the physical level: the main source of environmental disturbance in the marine hydrogen production scenario is wind. This application derives the data source required for PEM electrolyzer simulation from the wind field based on first principles, ensuring strict matching of the energy magnitude between the wave fluctuations and the electrical load at the PEM electrolyzer end, and has causal consistency. This simplifies the difficulty of data screening and matching, and eliminates the data logic conflict problem when multiple fields are coupled by using physical correlation.

[0022] 2. The PEM electrolyzer marine hydrogen production adaptability test method and test system described in this application reduces the difficulty of data acquisition and improves the robustness of the system: This test method only requires input of meteorological data, uses a virtual mapping algorithm to replace wave data acquisition, eliminates the need to deploy a buoy data acquisition system, reduces the need for hardware redundancy and data acquisition, and generally the acquisition of marine meteorological data is not easily affected by environmental interference, and reduces sensor links, which has high robustness in terms of data source and can reduce test costs.

[0023] 3. The PEM electrolyzer's method and system for testing the adaptability of hydrogen production at sea described in this application reconstructs low-frequency data to match the electrolyzer's response characteristics: by using physical operators to reconstruct low-frequency statistical information into high-frequency time-series signals, it can match the electrolyzer's response characteristics. In the case of limited data sources, it can establish a connection between macroscopic meteorological observation data and microscopic electrochemical reactions. The generated time-series data conforms to physical laws and can match the electrolyzer's response frequency band, thereby ensuring that the test can proceed normally.

[0024] 4. The PEM electrolyzer marine hydrogen production adaptability test method and test system described in this application has strong synchronization of multi-channel data output and acquisition: by aligning timestamps and unifying time steps to synchronize host computer data calculation, PLC data writing and acquisition, motor control, and power output, it can reduce the output and acquisition time difference introduced by the test link, reduce the asynchronous error between load and electrolyzer end response, and provide a high-fidelity data environment for the study of electrolyzer dynamic characteristics.

[0025] 5. The PEM electrolyzer marine hydrogen production adaptability test method and test system described in this application have regional mobility and can reproduce target sea conditions and scenarios: Since the test only relies on wind field input, this system can quickly reproduce the operating environment of a specific sea area by adjusting physical parameters such as wind path and water depth based on historical meteorological data of any target sea area, overcoming the limitations of on-site sea trials restricted by geographical location and broadening the scope of operating condition verification of hydrogen production equipment. Attached Figure Description

[0026] Figure 1 A flowchart illustrating the testing method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the structure of the test system provided in the embodiments of this application; Figure 3 A schematic diagram of the reconstructed time series of wind speeds at a height of 10 meters in the target sea area provided in an embodiment of this application; Figure 4 A comparison diagram between the single-sided power spectral density in the Kaimal spectrum and the theoretical Kaimal spectrum provided in the embodiments of this application; Figure 5 A schematic diagram of an instantaneous wavefront rise sequence provided in an embodiment of this application; Figure 6 A schematic diagram of the heave displacement time-series curve provided in the embodiments of this application; Figure 7 A schematic diagram of the pitch angle timing curve provided in the embodiments of this application; Figure 8 A schematic diagram of the wind speed time series at the height of the wind turbine hub provided in an embodiment of this application; Figure 9This is a schematic diagram of the mapped wind turbine power curve provided in an embodiment of this application.

[0027] In all the accompanying drawings, the same reference numerals are used to denote the same elements or structures, wherein: 10. Proton exchange membrane electrolyzer; 20. Six-degree-of-freedom platform; 30. Liquid supply unit; 31. Water tank; 32. Peristaltic pump; 33. Ultrapure water filtration device; 40. Power supply unit; 41. Programmable DC power supply; 50. Gas emission unit; 51. Hydrogen emission pipeline; 52. Hydrogen-side gas treatment device; 53. Hydrogen-side gas flow meter; 54. Hydrogen-side check valve; 55. Oxygen emission pipeline; 56. Oxygen-side gas treatment device; 57. Oxygen-side gas flow meter; 58. Oxygen-side check valve; 60. Temperature sensor; 61. Voltage sensor; 62. Current sensor; 70. Control and display unit; 71. Host computer; 72. Programmable logic controller; 80. Electrochemical workstation; 90. Gas analyzer. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0029] The following is in conjunction with the appendix Figure 1 -Appendix Figure 9 This application will be described in further detail.

[0030] Implementation Method 1: This application provides a method for testing the adaptability of PEM electrolyzers for offshore hydrogen production, such as... Figure 1 As shown, it includes the following steps: Step S1: Obtain a high-frequency pulsating wind speed time series with a frequency of not less than 10Hz based on the wind field data of the target sea area. .

[0031] Step S2: Based on the wind field data and high-frequency pulsating wind speed time series of the target sea area, map the wind field of the target sea area into a virtual wave field to obtain the instantaneous wave rise sequence.

[0032] Step S3: Establish a dynamic model of the hydrogen production platform in the target sea area, and combine the instantaneous wavefront rise sequence to calculate the multi-degree-of-freedom motion time history data of the hydrogen production platform in the target sea area.

[0033] Step S4: Based on the power model of the offshore power generation equipment, the meteorological characteristics of the target sea area are mapped to the output power of the offshore power generation equipment, so as to serve as the power input data of the electrolyzer in the hydrogen production platform.

[0034] Step S5: Align the multi-degree-of-freedom motion time history data and the power input data on the time scale, and use them as the control input source of the multi-degree-of-freedom platform below the electrolytic cell and the control input source of the power supply connected to the electrolytic cell, respectively, to synchronously simulate the mechanical fluctuations of ocean waves and the fluctuations of power load. Then, collect the physical field parameters during the operation of the electrolytic cell in real time.

[0035] The PEM electrolyzer offshore hydrogen production adaptability testing method described in this application can simulate the in-situ hydrogen production scenario of PEM water electrolyzer with offshore wind power, couple ocean wave fluctuations and wind power fluctuations, and eliminate data logic conflicts in multi-field coupling by utilizing physical correlation. In terms of data processing and generation, a coherent ocean wave-power fluctuation generation method can be established by using wind energy as a single data source, which simplifies the difficulty of scenario matching and data acquisition, and provides a testing scheme for the offshore adaptability testing and development of PEM electrolyzers.

[0036] The following section will provide a detailed description of the specific procedures for each step of the testing method described in this application.

[0037] In step S1, environmental feature extraction and wind field temporal reconstruction are performed, as detailed below.

[0038] The raw wind field data of the target sea area is acquired, mainly including the wind speed vector component at a height of 10m above sea level. The sampling frequency of the raw wind field data is evaluated. If it is low-frequency statistical data, a pulsating wind speed spectrum model is used to perform dynamic downscaling on the wind field data to reconstruct a high-frequency pulsating wind speed time series with a frequency of not less than 10Hz. .

[0039] Generally, publicly available meteorological data (wind speed) is on an hourly timescale, with some local meteorological resource databases reaching minute-level. This data frequency is too low for electrolytic cell operation, necessitating downscaling of low-frequency statistical data. However, if sea conditions in the target area permit, offshore wind field data can be obtained through on-site measurements. High-frequency pulsating wind speed time series can be obtained by directly collecting wind speed data in the target sea area at a sampling frequency of at least 10Hz, thus eliminating the need for downscaling.

[0040] If the original wind field data for the target sea area is low-frequency wind speed data, then the Kaimal fluctuating wind speed spectrum model needs to be used to perform dynamic downscaling of the wind field data in order to reconstruct and generate a high-frequency fluctuating wind speed time series. The specific steps include: Step S11: Obtain the eastward wind speed component at a predetermined height above sea level. and northward wind speed component The average wind speed was calculated using a vector method. and weather wind direction Preferably, the wind speed component is collected at a height of 10m above the sea level in the target sea area.

[0041] The average wind speed was calculated using the vector synthesis method. As an energy benchmark for pulsating wind fields, meteorological wind direction Used to determine the main direction of subsequent wave propagation and the yaw angle of the hydrogen production platform.

[0042] Step S12: Construct the Kaimal spectrum of energy distribution in the frequency domain and obtain the one-sided power spectral density of the longitudinal fluctuating wind speed component. , Let be the standard deviation of wind speed fluctuation, and , For turbulence integral scale parameters, The turbulence intensity at a predetermined height. This refers to the frequency of the pulsating wind.

[0043] Standard deviation of wind speed fluctuation The method for calculating the intensity of wind field fluctuation energy is as follows: ; Turbulent integral scale parameters The average spatial size of the turbulent vortex; the turbulence intensity at the target height. This reflects the severity of wind speed fluctuations; and These two parameters can be determined by parameters such as sea surface roughness and wind speed, referring to IEC standards.

[0044] Step S13: Calculate the single-sided power spectral density Frequency-to-time domain transformation yields the pulsating time series (pulsating wind speed). ).

[0045] First, the obtained continuous spectral function is discretized in the frequency domain, with frequency intervals... Will The frequency range is divided into N discrete frequency points. Calculate each discrete frequency point Corresponding harmonic component amplitude , where k is an integer from 1 to N.

[0046] Subsequently, to simulate the uncertainty of natural wind fields, a random phase sequence was generated. Then the fluctuating wind speed is calculated. Alternatively, the inverse fast Fourier transform can be used to obtain the fluctuating wind speed. t is a time variable.

[0047] Step S14: Based on the average wind speed obtained in Step S11 and the fluctuating wind speed obtained in Step S13, and according to the time-domain composition of the actual wind speed, a high-frequency fluctuating wind speed time series representing the actual wind speed in the target sea area can be obtained. .

[0048] In step S2, the wind field is mapped to a virtual wave field, as detailed below.

[0049] Wave spectrum characteristic parameters were obtained based on wind field data of the target sea area, and Jonswap random wave spectrum was constructed to obtain instantaneous wave rise sequences. Specifically, it includes the following steps: Step S21: Based on the wind field data and high-frequency pulsating wind speed time series of the target sea area, calculate the dimensionless wind path using empirical formulas for wind and wave development. And thus, the effective wave height can be calculated. Spectral peak period , For the wind direction in the target sea area, The gravitational acceleration of the target sea area.

[0050] Step S22: Based on the significant wave height and spectral peak period, construct the Jonswap random wave spectrum suitable for nearshore areas with limited wind path, with the wave power spectral density being: , The angular frequency of the spectral peak. For peak enhancement factor, The energy balance coefficient, For peak shape parameters, ω is the angular frequency.

[0051] Among them, the spectral peak angular frequency Spectral peak enhancement factor Typically, it is taken as 3.3; energy balance coefficient With significant wave height Related: ;when At that time, peak shape parameter Take 0.07; when At that time, peak shape parameter Take 0.09.

[0052] Step S23: Analyze the wave power spectral density A frequency-to-time domain transformation is performed to obtain the instantaneous wavefront elevation sequence.

[0053] First, the obtained continuous power density spectrum is discretized by frequency intervals. Will The frequency range is divided into N discrete frequency points, and the calculation is performed for each discrete frequency point. Corresponding harmonic component amplitude n takes any integer from 1 to N.

[0054] Subsequently, to deduce the motion characteristics of the hydrogen production platform, the sequence was converted into complex form, and the wave spectrum was transformed from the frequency domain to the time domain using inverse fast Fourier transform to obtain the instantaneous wave rise sequence, providing a verifiable benchmark for wave reconstruction. First, a random phase sequence was generated. Then construct the complex spectrum of the wavefront. The instantaneous wavefront rise sequence was obtained by using inverse fast Fourier transform. .

[0055] According to one embodiment of this application, based on step S24, a statistical method is used to calculate the instantaneous wave rise sequence to obtain the effective wave height for the virtual wave field. ,Will and The comparison was used to assess the accuracy of the virtual wave field in representing the target sea area.

[0056] Specifically, obtaining the effective wave height of the virtual ocean wave field. Includes the following steps: Step S24: Based on the instantaneous wavefront rise sequence The zero-crossing point divides it into k independent wave intervals. .

[0057] When dividing a wave sequence, the starting point of the wave is defined as the crossover point above zero. If the conditions are met This is counted as the start of a wave. In discrete sequences, it simplifies to: when If the conditions are met This is counted as the beginning of a wave.

[0058] Step S25: Based on the wave peaks within each wave interval and trough Calculate single wave height To obtain the wave height set .

[0059] Step S26: Sort the wave height set from largest to smallest and calculate the number of points in the first 1 / 3. Then calculate the average value to obtain the effective wave height. In actual testing, it can be Compared with the calculation in step S21 A comparison is made to serve as a verification metric for the virtual wave field in step S2.

[0060] Since the instantaneous wave rise sequence is obtained from the wave spectrum and energy frequency domain, a statistical method is used to calculate the generated wave rise frequency to ensure the logical closed loop of the verification process, thereby obtaining the effective wave height for the virtual wave field. .

[0061] In step S3, the motion response calculation of the floating carrier is performed, as detailed below.

[0062] A dynamic model of the hydrogen production platform within the target sea area is established, and the multi-degree-of-freedom motion time history data of the hydrogen production platform within the target sea area is calculated by combining the instantaneous wavefront rise sequence. Specifically, the following steps are included: Step S31: Establish a dynamic model of the hydrogen production platform in the target sea area. Based on the wind direction angle information and the installation direction of the hydrogen production platform, obtain the amplitude response operator matrix at the corresponding incident angle, including the amplitude response with angular frequency at six degrees of freedom. Variation amplitude operator With phase operator , where i is an integer from 1 to 6.

[0063] Step S32: Analyze the complex spectrum of the wavefront. By performing frequency domain convolution with the amplitude operators of each degree of freedom, the complex spectrum of the motion components under the corresponding degrees of freedom is obtained. ; Step S33: Perform inverse fast Fourier transform on the complex spectra under each of the above degrees of freedom to obtain time-domain motion sequences of not less than 10Hz. The value of N is the same as in step S2, thus obtaining the attitude matrix of the offshore hydrogen production platform. .

[0064] Step S34: Convert the attitude matrix The six-degree-of-freedom time history data of the offshore hydrogen production platform is input into the multi-degree-of-freedom platform to solve the corresponding motion control data.

[0065] Preferably, the multi-degree-of-freedom platform uses a Stewart mechanism with six degrees of freedom.

[0066] In step S4, dynamic mapping of the fluctuation input is performed, as detailed below.

[0067] If offshore power generation equipment uses wind turbines, based on the power characteristic model of the wind turbines, the high-frequency pulsating wind speed time series is mapped to the power generation curve of the wind turbines, which can then be used as the power input curve of the electrolyzer.

[0068] If photovoltaic (PV) equipment is used for offshore power generation, the solar irradiance data of the target sea area is mapped to the power generation curve of the PV equipment based on the power characteristic model of the PV equipment, so as to serve as the power input curve of the electrolyzer.

[0069] If offshore power generation equipment uses wind turbines and photovoltaic equipment, based on the power characteristic models of wind turbines and photovoltaic equipment, the high-frequency pulsating wind speed time series and the solar irradiance data of the target sea area are mapped to the power generation curves of wind turbines and photovoltaic equipment, respectively. The two power generation curves are superimposed as the power input curve of the electrolyzer.

[0070] Taking offshore power generation equipment using wind turbines as an example, mapping the high-frequency pulsating wind speed time series to the power generation curve of the wind turbine specifically includes the following: Step S41: First, based on the operating characteristics of the wind turbine, determine the instantaneous wind speed at a height of 10 meters. Mapped to wind speed at the height of the wind turbine hub According to IEC standards, for offshore wind power scenarios, wind speed is extrapolated using an exponential law: , The wind shear index is typically taken as 0.11 for offshore scenarios. This refers to the height of the wind turbine hub.

[0071] Step S42: Next, based on the power output characteristics of the wind turbine, the wind speed at the height of the wind turbine hub is converted into the power generation curve of the wind turbine.

[0072] Specifically, depending on wind speed The relationship between the wind speed and the set wind speed of each fan, and the wind speed This is mapped to the power generation capacity of the wind turbine.

[0073] when At that time, the wind turbine operates with a constant pitch, and the wind turbine's power generation curve is as follows: .

[0074] when At that time, the wind turbine operates at its rated power, and the wind turbine's power generation curve is as follows: .

[0075] when or At that time, the power generation curve of the wind turbine was .

[0076] in, air density; The radius of the wind turbine blades; Wind energy utilization coefficient; The tip speed ratio; The blade pitch angle; This refers to the rated power of the fan. To cut in wind speed; Rated wind speed; To cut off the wind speed.

[0077] According to one embodiment of this application, based on step S42, taking into account the relationship and response delay of the wind turbine system, the actual output can be simulated using inertial equations.

[0078] Specifically, the first-order inertial equation is adopted. The dynamic response delay of the wind turbine's output power being transferred to the electrolyzer is simulated, and the following is also performed. This is the actual power input curve of the electrolyzer.

[0079] Preferably, step S4 can also use fan simulation software to obtain the fan output curve as the power input of the electrolyzer.

[0080] In step S5, hardware execution and data acquisition are performed, as detailed below.

[0081] The multi-degree-of-freedom motion time history data obtained in step S3 and the electrolytic cell power input data obtained in step S4 are aligned on a time scale and a high-precision timestamp is added. After pre-calculation by the computer, the data is grouped and written into the data buffer block of the test bench PLC according to the time sequence. Through the clock beat in the PLC, the data is written into the motor drive module of the multi-degree-of-freedom platform and the power supply connected to the electrolytic cell according to the timestamp, so as to synchronously simulate the mechanical fluctuation of ocean waves and the fluctuation of power load. Preferably, a six-degree-of-freedom platform (i.e., the Stewart mechanism mentioned above) is selected for the multi-degree-of-freedom platform, and a programmable DC power supply is selected for the power supply.

[0082] At each time step, the PLC triggers the sensor array to collect physical field parameters (including but not limited to temperature, current, voltage, gas flow rate, etc.) during the operation of the electrolytic cell in real time, and returns the relevant data with the same source timestamp to the host computer for storage and analysis.

[0083] Ideally, the host computer and PLC can be synchronized via the PTP protocol, thereby achieving time synchronization of multi-channel data acquisition and facilitating subsequent data processing and analysis of response characteristics.

[0084] The test method described in the application will be explained below with reference to a specific embodiment.

[0085] Wind speed information for a specific period in a target sea area can be obtained by using publicly available historical meteorological databases (such as ERA5). Hourly data from a certain offshore wind farm was used in this study. , According to the World Meteorological Organization (WMO) requirements for meteorological data format specifications, u is the vector component along the latitude direction with due east as the positive direction, and v is the vector component along the longitude direction with due north as the positive direction. Thus, wind direction data can be derived from single-source wind speed data.

[0086] Step 1: Extract environmental features and reconstruct the wind field, as detailed below.

[0087] The average wind speed is: ; The meteorological wind direction is: ; Weather and wind direction It is in the northeast-east direction.

[0088] Set Kaimal spectrum parameters: sampling frequency The frequency is 10Hz; the total duration T is 1h (3600s); there are a total of 36,000 sampling points N.

[0089] Referencing IEC standards, set the turbulence intensity. 15%, longitudinal turbulence integral scale Given a depth of 170m, the standard deviation of wind speed can be calculated: ; Construct the one-sided power spectral density function of the longitudinal fluctuating wind speed component: ; in For the frequency of pulsating wind, Frequency resolution .

[0090] At each discrete frequency point Calculate the corresponding harmonic amplitude : ; Constructing frequency domain eigenvectors in complex form : ; in, ， It is a random phase sequence.

[0091] Performing an IFFT transform converts the frequency domain signal into a time domain ripple component. ; Obtain the time series sequence of fluctuating wind speed The wind speed time series at a height of 10 meters is as follows: Figure 3 As shown. A uniform timestamp is then appended to the generated sequence, serving as the driving force for subsequent steps.

[0092] The above method introduces a feature The Kaimal spectral operator with a 5 / 3 power law characteristic ensures that the reconstructed high-frequency wind field conforms to the Kolmogorov energy level law of atmospheric boundary layer turbulence in terms of energy evolution logic. For example... Figure 4As shown, the energy density of the reconstructed sequence spectrum is compared with the theoretical spectrum, and the two match well. The wind speed data is downscaled without changing the energy spectrum characteristics, which solves the problem that hourly meteorological data cannot characterize the micro-transient load of the electrolyzer.

[0093] Step 2: Map the wind field to a virtual ocean wave field, as follows.

[0094] Based on the target sea state, wind path The feature size is 55km, and the gravitational acceleration of the target area is... It is 9.7863 ; Calculate the dimensionless wind path: ; Significant wave height: ; Spectral peak period: ; Compare with actual sea state data: , ， The relative error of significant wave height was 12.83%, and the relative error of spectral peak period was 10.31%, both less than 15%. According to the World Meteorological Organization's (WMO) evaluation criteria for model accuracy in its "Guidelines for Wave Analysis and Forecasting," this level of error indicates that the calculated simulation data and the actual physical sea conditions have high mapping accuracy at the statistical dynamics level, and the scene can be considered to have high fidelity. The main sources of error are the differences in wave development, including non-steady-state characteristics and the spatial smoothness of reanalysis data. This method does not consider the influence of water depth and environment on wave development.

[0095] Based on the obtained effective wave height and spectral peak period, a Jonswap random wave spectrum suitable for nearshore finite wind range sea areas is constructed to describe the frequency domain energy distribution of waves: ; Among them, the spectral peak angular frequency Spectral peak enhancement factor Take 3.3; Energy balance coefficient With significant wave height Related: ;when At that time, peak shape parameter Take 0.07; when At that time, peak shape parameter Take 0.09.

[0096] frequency range Divided into N equidistant frequency micro elements Each frequency point Calculate the corresponding amplitude : ; Constructing the complex spectrum: ; in, ， It is a random phase sequence, where n is an integer from 1 to N.

[0097] Performing an IFFT transform yields the instantaneous wavefront rise sequence. ,like Figure 5 As shown.

[0098] Step 3: Calculate the motion response characteristics of the floating carrier, as detailed below.

[0099] The target platform is a 30m×30m moored platform. The Doppler frequency shift of the platform can be ignored. Due to the characteristics of the moored platform, the spatial motion of the platform is idealized, and its displacement along the sea level (x and y direction displacement) and its axial rotation (z direction rotation) are ignored.

[0100] The amplitude operator of the simplified platform is described here. With phase operator Let 0.8 rad / s be the resonance point, for each frequency point... The complex spectrum of the motion components of the platform in the i-th degree of freedom is calculated as follows: ; Then perform IFFT transformation. Thus, the heave displacement and pitch angle of the platform with six degrees of freedom are obtained, as shown below. Figure 6 and Figure 7 As shown.

[0101] The heave displacement corresponds to the displacement perpendicular to the sea level (displacement in the z direction). By combining the wind direction and the pitch angle, multiplying the pitch angle by the sine and cosine of the wind direction respectively, we can obtain the platform's sway (rotation in the x and y directions).

[0102] The kinematics were then used to calculate the stroke data for each of the six servo motors within the Stewart mechanism.

[0103] Step 4: Perform fluctuation input mapping, as follows.

[0104] Based on the power characteristic model of the wind turbine, the power generation curve of the wind turbine is calculated using empirical formulas from the high-frequency pulsating wind speed time series obtained in the first step. The wind turbine parameters are as follows: rated power... Cut-in wind speed: Rated wind speed Cut off the wind speed Local air density blade radius Wind turbine hub height Maximum wind energy utilization coefficient Equivalent response time constant of the wind turbine system System power conversion efficiency .

[0105] Extrapolate the wind speed time series at a height of 10 meters to the hub height: ; The wind speed at the height of the wind turbine hub obtained from the reconstruction is as follows: Figure 8 As shown.

[0106] when At this time, the wind turbine operates at a constant pitch: ; when At that time, the fan operates at its rated power: ; At other wind speeds .

[0107] The relationships and response delays of the wind turbine system can be simulated using first-order inertial equations: ; Obtain the wind turbine output curve like Figure 9 As shown, This is the actual power input curve of the electrolyzer.

[0108] Step 5: Perform hardware execution and testing, as detailed below.

[0109] After assembling the corresponding testing equipment (completing the installation of the six-degree-of-freedom platform, programmable DC power supply, detection components, and PLC, etc.), enable the PTP protocol in the host computer, set the network card as the master clock, and synchronize the internal clock of the host computer; on the PLC side, select time synchronization via PTP protocol in the synchronization method, and set the PLC as a slave station.

[0110] The motor running timing data and power supply fluctuation data of the six-degree-of-freedom platform are divided into blocks according to the data volume and written into the programmable DC power supply memory and PLC data block. In this embodiment, one hour of data is simulated and can be written directly. A unified hardware start signal is set for the power supply and servo drive system, the status of the sensors and other detection instruments is checked, and the timing of the acquisition card, PLC acquisition module and detection instruments is aligned.

[0111] After the test system and wave-power fluctuation data are prepared, an external hardware trigger button is set. After the external trigger is set, the PLC synchronously sends a start signal to the servo control system and the programmable DC power supply. The servo control system and the programmable DC power supply operate according to the fluctuation data in their internal data memory and the unified time rhythm issued by the host computer. The sensors connected to the PLC and the host computer acquisition card match the fluctuation data according to the time information of the host computer and collect data such as temperature, voltage, current, and flow rate at a frequency of 10Hz, and store them with timestamps in the host computer storage medium.

[0112] Simultaneously, an electrochemical workstation is set up to perform electrochemical tests during the electrolysis process. A data acquisition window is set during the test, during which the six-degree-of-freedom platform and programmable DC power supply are set to the steady-state state for the current time period. The electrochemical workstation's swept-frequency AC impedance function is then activated to test the electrolytic cell impedance spectrum. After the impedance spectrum test is completed, the absolute time is recorded by the host computer. Then, the six-degree-of-freedom platform and programmable DC power supply are simultaneously activated to execute the fluctuation output according to the time sequence. In long-term cyclic tests, the electrochemical impedance spectrum test interval should ideally be no less than 1 hour. For scanning voltage tests performed by the electrochemical workstation, it is recommended to measure before and after the fluctuation test, and not during operation. During measurement, the external DC power supply must be kept off.

[0113] Simultaneously, a gas analyzer is set up to analyze the gas generated during the electrolysis test. The gas analyzer adopts an online continuous test mode. The time record of the test software uses the host computer network card clock, and the recorded absolute time data is stored in the host computer storage medium.

[0114] Implementation Method Two: This application also provides a PEM electrolyzer for testing the adaptability of hydrogen production at sea, which is used to implement the PEM electrolyzer for testing the adaptability of hydrogen production at sea as described in Embodiment 1. Figure 2 As shown, the test system includes: a proton exchange membrane electrolyzer 10; a six-degree-of-freedom platform 20, on which the proton exchange membrane electrolyzer 10 is placed and moves with the platform to simulate the wave-like conditions of hydrogen production at sea; a liquid supply unit 30 connected to the proton exchange membrane electrolyzer 10 to supply it with electrolyzed water; a power supply unit 40 connected to the proton exchange membrane electrolyzer 10 to simulate the power supply of offshore power generation equipment to the proton exchange membrane electrolyzer 10; a gas emission unit 50 connected to the proton exchange membrane electrolyzer 10 to discharge the gas generated by the electrolysis reaction; a sensor monitoring unit used to collect parameters of the proton exchange membrane electrolyzer 10 during the electrolysis reaction process; and a control and display unit 70 connected to the six-degree-of-freedom platform 20, the power supply unit 40, and the sensor monitoring unit to control and acquire signals from each part of the test system.

[0115] The PEM electrolyzer offshore hydrogen production adaptability testing system described in this application can simulate the offshore wind power in-situ hydrogen production scenario using a PEM water electrolyzer. By controlling the six-degree-of-freedom platform 20 and the power supply unit 40, and coupling wave fluctuations with wind power fluctuations, it can effectively reduce the interference of time differences between various instruments and equipment on the measurement of the dynamic response characteristics of the electrolyzer during the test, and more accurately evaluate the offshore adaptability of the electrolyzer.

[0116] The following section will provide a detailed description of the specific structure of each part of the PEM electrolyzer marine hydrogen production adaptability testing system described in this application, as well as the location and connection relationships between each part.

[0117] The six-degree-of-freedom platform 20 uses a Stewart mechanism to simulate the wave conditions of hydrogen production at sea. The telescopic arms in the Stewart mechanism are all driven by servo motors, and the speed and acceleration required by the platform should match the calculated wave conditions.

[0118] like Figure 2 As shown, the proton exchange membrane electrolyzer 10 is fixedly mounted on a six-degree-of-freedom platform 20 and can move in six directions in space under the drive of the six-degree-of-freedom platform 20. The proton exchange membrane electrolyzer 10 includes end plates, electrodes, flow channel mesh, gaskets, membrane electrodes, etc., and relevant components can be replaced as needed.

[0119] like Figure 2 As shown, the liquid supply unit 30 includes a water tank 31, a peristaltic pump 32, and an ultrapure water filtration device 33 connected in sequence. The outlet of the ultrapure water filtration device 33 is connected to the inlet of the proton exchange membrane electrolyzer 10 through a pipe, and the outlet of the proton exchange membrane electrolyzer 10 is connected to the return port of the water tank 31 through a pipe.

[0120] Regarding water circulation in the electrolyzer, such as Figure 2 As shown, the devices in the liquid supply unit 30 are connected by nylon tubes. Deionized water starts from the water tank 31 and, driven by the peristaltic pump 32, passes through the ultrapure water filtration device 33 (including a deionized resin filter and a conductivity sensor) and enters the proton exchange membrane electrolyzer 10. The water returning from the proton exchange membrane electrolyzer 10 and the water separated from the hydrogen side flow back to the water tank 31. Deionized water is pre-added to the water tank 31.

[0121] Preferably, the water tank 31 is a double-layered insulated water tank, which is equipped with a heater. The tank is equipped with a liquid level sensor and a water pump, which can heat the filtered ultrapure water or pure water and automatically replenish the water volume according to the liquid level. The heater is a temperature-settable constant temperature heater, which can adjust the temperature inside the water tank 31 according to the temperature sensor feedback at the inlet of the proton exchange membrane electrolyzer 10.

[0122] like Figure 2 As shown, the power supply unit 40 includes a programmable DC power supply 41. The positive and negative terminals of the programmable DC power supply 41 are connected to the two ends (cathode and anode) of the proton exchange membrane electrolyzer 10 via wires, respectively. The programmable DC power supply 41 is used to supply power to the proton exchange membrane electrolyzer 10, enabling power fluctuation adaptability testing of the water electrolysis hydrogen production system according to GB / T46104-2025. It can also cooperate with the six-degree-of-freedom platform 20 to complete power fluctuation simulation of marine hydrogen production.

[0123] like Figure 2 As shown, the gas emission unit 50 includes a hydrogen emission line 51 and an oxygen emission line 55, both connected to the proton exchange membrane electrolyzer 10. The hydrogen emission line 51 and the oxygen emission line 55 are arranged side by side. The hydrogen emission line 51 is used to collect and emit hydrogen generated during the electrolysis test, and the oxygen emission line 55 is used to collect and emit oxygen generated during the electrolysis test. The hydrogen emission line 51 is sequentially equipped with a hydrogen-side gas treatment device 52, a hydrogen-side gas flow meter 53, and a hydrogen-side check valve 54; the oxygen emission line 55 is sequentially equipped with an oxygen-side gas treatment device 56, an oxygen-side gas flow meter 57, and an oxygen-side check valve 58.

[0124] like Figure 2 As shown, the sensor monitoring unit includes a temperature sensor 60, a voltage sensor 61, and a current sensor 62. The temperature sensor 60 is located between the layers of the proton exchange membrane electrolyzer 10 or at the water / gas inlet / outlet of the proton exchange membrane electrolyzer 10, and is used to collect the temperature during the electrolysis test. The voltage sensor 61 is located between the positive and negative electrodes of the proton exchange membrane electrolyzer 10, specifically connected to the two tabs of the proton exchange membrane electrolyzer 10, and is used to collect the voltage between the positive and negative electrodes during the electrolysis test. The current sensor 62 is located on the wire connecting the power supply unit 40 and the proton exchange membrane electrolyzer 10; preferably, the current sensor 62 is located on the wire connected to the positive electrode tab, and is used to collect the current during the electrolysis test.

[0125] like Figure 2 As shown, the control and display unit 70 includes a host computer 71 and a programmable logic controller 72; the programmable logic controller 72 is connected to the six-degree-of-freedom platform 20, the liquid supply unit 30, the power supply unit 40 and the sensor monitoring unit; the host computer 71 is connected to the programmable logic controller 72 and the gas emission unit 50.

[0126] Specifically, such as Figure 2As shown, each sensor in the sensor monitoring unit is connected to the corresponding port on the programmable logic controller (PLC) 72 according to its protocol type, so as to acquire data during the electrolysis test through the PLC 72. The peristaltic pump 32 and the programmable DC power supply 41 are equipped with hardware triggering and data pre-storage functions, and are connected to the corresponding port on the PLC 72, so as to control the peristaltic pump 32 and the programmable DC power supply 41 through the PLC 72. The gas flow meter is connected to the acquisition card on the host computer 71 according to its protocol type, and can record and display the acquired flow data in real time on the host computer 71. The host computer 71 is connected to the PLC 72, and can program and control the PLC 72 while receiving the data acquired by the PLC 72.

[0127] The host computer 71 stores a computer-readable program that executes the method described in Embodiment 1. After the initial data required for the test method is input into the host computer 71, the host computer 71 executes the above program and outputs the corresponding results. Then, the host computer 71 sends the corresponding results (control signals) to the drive controller of the servo motor and the programmable DC power supply in the six-degree-of-freedom platform 20 through the PLC, thereby simulating the mechanical fluctuations of sea waves and power fluctuations caused by sea winds.

[0128] According to one embodiment of this application, such as Figure 2 As shown, the testing system also includes an electrochemical workstation 80. The test port of the electrochemical workstation 80 is electrically connected to the wires located between the power supply unit 40 and the proton exchange membrane electrolyzer 10. The information transmission port of the electrochemical workstation 80 is electrically connected to the host computer 71. The electrochemical workstation 80 generally has five signal acquisition interfaces, including a working electrode (WE), a working sensing electrode (WS), a reference electrode (RE), a counter electrode (CE), and a ground electrode (GND). The WE and WS electrodes are electrically connected to the anode of the proton exchange membrane electrolyzer 10, the RE and CE electrodes are electrically connected to the cathode of the proton exchange membrane electrolyzer 10, and the GND electrode is connected to the outer shell of the proton exchange membrane electrolyzer 10.

[0129] According to one embodiment of this application, such as Figure 2 As shown, the testing system also includes a gas analyzer 90. The input terminal of the gas analyzer 90 is connected to the gas emission unit 50, and the information transmission port of the gas analyzer 90 is electrically connected to the host computer 71. Specifically, the gas inlet of the gas analyzer 90 is connected to the outlet of the hydrogen-side check valve 54, and the gas outlet is connected to the hydrogen emission interface. The information transmission port for data transmission is connected to the acquisition card on the host computer 71 according to its protocol type, and can record and display gas analysis data on the host computer 71.

[0130] It should be understood that expressions such as "comprising" and "may include" as used in this application indicate the existence of the disclosed functions, operations, or constituent elements, and do not limit one or more additional functions, operations, and constituent elements. In this application, terms such as "comprising" and / or "having" may be interpreted as indicating a specific characteristic, number, operation, constituent element, component, or combination thereof, but should not be interpreted as excluding the existence or possibility of adding one or more other characteristics, numbers, operations, constituent elements, components, or combinations thereof.

[0131] It should be understood that the terms “center,” “upper,” “lower,” “front,” “rear,” “left,” “right,” “vertical,” “horizontal,” “inner,” “outer,” “clockwise,” “counterclockwise,” “axial,” “radial,” and “circumferential” indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0132] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0133] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0134] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for testing the adaptability of PEM electrolyzers for offshore hydrogen production, characterized in that, include: Obtain a high-frequency pulsating wind speed time series with a frequency of no less than 10Hz based on wind field data of the target sea area. ; Based on the wind field data of the target sea area and the high-frequency pulsating wind speed time series, the wind field of the target sea area is mapped into a virtual wave field to obtain the instantaneous wave rise sequence. A dynamic model of the hydrogen production platform in the target sea area is established, and the multi-degree-of-freedom motion time history data of the hydrogen production platform in the target sea area is calculated by combining the instantaneous wavefront rise sequence. The meteorological characteristics of the target sea area are mapped to the output power of the offshore power generation equipment based on the power model of the offshore power generation equipment, so as to serve as the power input data of the electrolyzer in the hydrogen production platform. The multi-degree-of-freedom motion time history data and the power input data are aligned on the time scale, and the two are used as the control input source of the multi-degree-of-freedom platform below the electrolytic cell and the control input source of the power supply connected to the electrolytic cell, respectively, to synchronously simulate the mechanical fluctuations of ocean waves and the fluctuations of power load. Then, the physical field parameters during the operation of the electrolytic cell are collected in real time.

2. The method for testing the adaptability of PEM electrolyzers for offshore hydrogen production according to claim 1, characterized in that, The high-frequency pulsating wind speed time series with a frequency of not less than 10Hz obtained from the wind field data of the target sea area includes: The high-frequency pulsating wind speed time series is obtained by directly collecting samples at a sampling frequency of not less than 10Hz in the target sea area; or, after obtaining the low-frequency wind speed data of the target sea area, the wind field data is dynamically downscaled using the Kaimal pulsating wind speed spectrum model to reconstruct and generate the high-frequency pulsating wind speed time series.

3. The method for testing the adaptability of PEM electrolyzers for offshore hydrogen production according to claim 2, characterized in that, The dynamic downscaling of the wind field data using the Kaimal fluctuating wind speed spectrum model includes: Obtain the eastward and northward wind speed components at a predetermined height above sea level, and calculate the average wind speed based on the wind speed components in both directions using a vector method. and weather and wind direction; Construct the Kaimal spectrum of wind energy distribution in the frequency domain and obtain the one-sided power spectral density of the longitudinal fluctuating wind speed component. , The standard deviation of wind speed fluctuation, For turbulent integral scale parameters, This refers to the frequency of pulsating wind. For the single-sided power spectral density A frequency-to-time domain transformation is performed to obtain a pulsating time sequence; The high-frequency pulsating wind speed time sequence is obtained by superimposing the pulsating time sequence with the average wind speed.

4. The method for testing the adaptability of PEM electrolyzers for offshore hydrogen production according to claim 1, characterized in that, Based on the wind field data of the target sea area and the high-frequency pulsating wind speed time series, the wind field of the target sea area is mapped to a virtual wave field to obtain the instantaneous wave rise sequence, including: Based on the wind field data of the target sea area and the high-frequency pulsating wind speed time series, the significant wave height is calculated using empirical formulas for wind and wave development. And spectral peak period; Based on the significant wave height and the spectral peak period, a Jonswap random wave spectrum suitable for nearshore sea areas with limited wind path is constructed, and its wave power spectral density is obtained. , The angular frequency of the spectral peak. As the peak enhancement factor, The energy balance coefficient, For peak shape parameters, Angular frequency, The gravitational acceleration of the target sea area; For the wave power spectral density The instantaneous wavefront elevation sequence is obtained by performing a frequency domain-to-time domain transformation.

5. The method for testing the adaptability of PEM electrolyzers for offshore hydrogen production according to claim 4, characterized in that, The effective wave height for the virtual wave field is obtained by calculating the instantaneous wave rise sequence using statistical methods. ,Will and The comparison is used to evaluate the fidelity of the virtual wave field to the target sea area.

6. The method for testing the adaptability of PEM electrolyzers for offshore hydrogen production according to claim 4, characterized in that, A dynamic model of the hydrogen production platform within the target sea area is established, and the multi-degree-of-freedom motion time history data of the hydrogen production platform within the target sea area is calculated by combining the instantaneous wavefront rise sequence, including: A dynamic model of the hydrogen production platform within the target sea area is established. Based on the wind direction angle information and the installation direction of the hydrogen production platform, the amplitude response operator matrix at the corresponding incident angle is obtained, including the amplitude response operator matrix with respect to angular frequency at six degrees of freedom. The magnitude and phase operators of the change; The wave power spectral density will be analyzed. The wavefront complex spectrum obtained during the frequency-to-time domain transformation is convolved with the amplitude operators of each degree of freedom in the frequency domain to obtain the complex spectrum of the motion components under the corresponding degree of freedom. The complex spectra under each of the above degrees of freedom are subjected to inverse fast Fourier transform to obtain a time-domain motion sequence of not less than 10Hz, and then the attitude matrix of the offshore hydrogen production platform is obtained. The attitude matrix is ​​used as the six-degree-of-freedom time history data of the offshore hydrogen production platform and input into the multi-degree-of-freedom platform to solve the corresponding motion control data.

7. The method for testing the adaptability of PEM electrolyzers for offshore hydrogen production according to claim 1, characterized in that, The power model based on the offshore power generation equipment maps the meteorological characteristics of the target sea area to the output power of the offshore power generation equipment, and serves as the power input data for the electrolyzer within the hydrogen production platform, including: The offshore power generation equipment uses a wind turbine. Based on the power characteristic model of the wind turbine, the high-frequency pulsating wind speed time series is mapped to the power generation curve of the wind turbine, which is used as the power input curve of the electrolyzer. Alternatively, the offshore power generation equipment may be a photovoltaic device. Based on the power characteristic model of the photovoltaic device, the solar irradiance data of the target sea area may be mapped to the power generation curve of the photovoltaic device, which may then be used as the power input curve of the electrolyzer. Alternatively, the offshore power generation equipment may employ wind turbines and photovoltaic devices. Based on the power characteristic models of the wind turbines and the photovoltaic devices, the high-frequency pulsating wind speed time series and the solar irradiance data of the target sea area are mapped to the power generation curves of the wind turbines and the photovoltaic devices, respectively. The two power generation curves are superimposed and used as the power input curve of the electrolyzer.

8. The method for testing the adaptability of PEM electrolyzers for offshore hydrogen production according to claim 7, characterized in that, Mapping the high-frequency pulsating wind speed time series to the power generation curve of the wind turbine includes: The high-frequency pulsating wind speed time series is mapped to the wind speed at the height of the wind turbine hub using an exponential law. Based on the power output characteristics of the wind turbine, the wind speed at the height of the wind turbine hub is converted into the power generation curve of the wind turbine.

9. The method for testing the adaptability of PEM electrolyzers for offshore hydrogen production according to claim 8, characterized in that, The dynamic response delay when the output power of the fan is transferred to the electrolytic cell is simulated using an inertial equation, and the simulation output result is used as the actual power input curve of the electrolytic cell.

10. A PEM electrolyzer for testing the adaptability of hydrogen production at sea, used to implement the PEM electrolyzer for testing the adaptability of hydrogen production at sea as described in any one of claims 1-9, characterized in that, The testing system includes: Proton exchange membrane electrolyzer (10); A six-degree-of-freedom platform (20) is used, and the proton exchange membrane electrolyzer (10) is placed on the six-degree-of-freedom platform (20) and moves together with the six-degree-of-freedom platform (20) to simulate the wave fluctuation conditions of hydrogen production at sea; A liquid supply unit (30) is connected to the proton exchange membrane electrolyzer (10) to supply it with electrolyzed water; A power supply unit (40) is connected to the proton exchange membrane electrolyzer (10) to simulate the power supply of an offshore power generation device to the proton exchange membrane electrolyzer (10). The power supply unit (40) includes a programmable DC power supply (41). The positive and negative terminals of the programmable DC power supply (41) are respectively connected to the two ends of the proton exchange membrane electrolyzer (10) through wires. A gas emission unit (50) is connected to the proton exchange membrane electrolyzer (10) to discharge the gas generated by the electrolysis reaction; A sensor monitoring unit is used to monitor the parameters of the proton exchange membrane electrolyzer (10) during the electrolysis reaction process; The control and display unit (70) is connected to the six-degree-of-freedom platform (20), the power supply unit (40) and the sensor monitoring unit to realize the control and signal acquisition of each part of the test system.

11. The PEM electrolyzer marine hydrogen production adaptability testing system according to claim 10, characterized in that, The liquid supply unit (30) includes a water tank (31), a peristaltic pump (32), and an ultrapure water filter (33) connected in sequence by pipes. The outlet of the ultrapure water filter (33) is connected to the inlet of the proton exchange membrane electrolyzer (10) by pipes, and the outlet of the proton exchange membrane electrolyzer (10) is connected to the return outlet of the water tank (31) by pipes. And / or, the sensor monitoring unit includes a temperature sensor (60), a voltage sensor (61), and a current sensor (62); the temperature sensor (60) extends into the proton exchange membrane electrolyzer (10), the voltage sensor (61) is disposed between the positive and negative electrodes of the proton exchange membrane electrolyzer (10), and the current sensor (62) is disposed on the wire connecting the power supply unit (40) and the proton exchange membrane electrolyzer (10); And / or, the control display unit (70) includes a host computer (71) and a programmable logic controller (72); the programmable logic controller (72) is connected to the six-degree-of-freedom platform (20), the liquid supply unit (30), the power supply unit (40) and the sensor monitoring unit; the host computer (71) is connected to the programmable logic controller (72) and the gas emission unit (50).

12. The PEM electrolyzer marine hydrogen production adaptability testing system according to claim 10, characterized in that, The testing system also includes an electrochemical workstation (80), the test port of which is electrically connected to a wire disposed between the power supply unit (40) and the proton exchange membrane electrolyzer (10), and the information transmission port of the electrochemical workstation (80) is electrically connected to the control display unit (70); And / or, the test system further includes a gas analyzer (90), the input of which is connected to the gas emission unit (50), and the information transmission port of which is electrically connected to the control display unit (70).

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